A multi-objective optimization energy approach to predict the ligand conformation in a docking process

Authors:
Angelica Sandoval-Perez;David Becerra;Diana Vanegas;Daniel Restrepo-Montoya;Fernando Nino
Affiliations:
Bioinformatics and Intelligent Systems Research Laboratory, Universidad Nacional de Colombia, Bogota, Colombia, Computational Biology, Department Biologie, Universität Erlangen-Nürnber, ...;Bioinformatics and Intelligent Systems Research Laboratory, Universidad Nacional de Colombia, Bogota, Colombia, McGill Centre for Bioinformatics, McGill University, Montreal, Canada;Bioinformatics and Intelligent Systems Research Laboratory, Universidad Nacional de Colombia, Bogota, Colombia;Bioinformatics and Intelligent Systems Research Laboratory, Universidad Nacional de Colombia, Bogota, Colombia;Bioinformatics and Intelligent Systems Research Laboratory, Universidad Nacional de Colombia, Bogota, Colombia
Venue:
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
Year:
2013

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Abstract

This work proposes a multi-objective algorithmic method for modelling the prediction of the conformation and configuration of ligands in receptor-ligand complexes by considering energy contributions of molecular interactions. The proposed approach is an improvement over others in the field, where the principle insight is that a Pareto front helps to understand the tradeoffs in the actual problem. The method is based on three main features: (i) Representation of molecular data using a trigonometric model; (ii) Modelling of molecular interactions with all-atoms force field energy functions and (iii) Exploration of the conformational space through a multi-objective evolutionary algorithm. The performance of the proposed model was evaluated and validated over a set of well known complexes. The method showed a promising performance when predicting ligands with high number of rotatable bonds.